Soft polymer materials, which are similar to human tissues, have played critical roles in modern interdisciplinary research. Compared with conventional methods, 3D printing allows rapid prototyping ...and mass customization and is ideal for processing soft polymer materials. However, 3D printing of soft polymer materials is still in the early stages of development and is facing many challenges including limited printable materials, low printing resolution and speed, and poor functionalities. The present review aims to summarize the ideas to address these challenges. It focuses on three points: 1) how to develop printable materials and make unprintable materials printable, 2) how to choose suitable methods and improve printing resolution, and 3) how to directly construct functional structures/systems with 3D printing. After a brief introduction on this topic, the mainstream 3D printing technologies for printing soft polymer materials are reviewed, with an emphasis on improving printing resolution and speed, choosing suitable printing techniques, developing printable materials, and printing multiple materials. Moreover, the state‐of‐the‐art advancements in multimaterial 3D printing of soft polymer materials are summarized. Furthermore, the revolutions brought about by 3D printing of soft polymer materials for applications similar to biology are highlighted. Finally, viewpoints and future perspectives for this emerging field are discussed.
3D printing of soft polymer materials allows the rapid prototyping of functional soft architectures in a highly integrated way. Herein, the recent advancements in this emerging topic are reviewed based on a target to improve its printing speed, resolution, printable material, and functionalities. The trends of multimaterial 3D printing are discussed and the perspectives for this emerging field are provided.
A significant number of isolable silylenes are currently known. They have quickly developed from laboratory curiosities to useful ligands in metal‐mediated homogeneous catalysis. This includes their ...utilization in various catalytic transformations, such as C−C cross‐coupling, cyclotrimerization, hydroformylation, borylation, deuteration, hydrosilylation, amination, hydrogenation, and transfer semi‐hydrogenation reactions. Recent studies suggest that the silylene ligands surpass the steering properties of their phosphine and N‐heterocyclic carbene (NHC) analogues and provide excellent chemo‐, regio‐, and stereoselectivites. Mechanistic studies suggest that their promoted performance of metal‐mediated catalytic transformations results from a strong σ‐donor character along with cooperative effects of their SiII centers. This Minireview covers the most recent advances in the field.
No longer laboratory curiosities: Stable silylenes are a versatile family of powerful steering ligands that increase catalytic activity and selectivity. This Minireview covers the recent progress of silylene ligands in homogeneous catalysis.
Image captioning aims to automatically generate a natural language description of a given image, and most state-of-the-art models have adopted an encoder-decoder framework. The framework consists of ...a convolution neural network (CNN)-based image encoder that extracts region-based visual features from the input image, and an recurrent neural network (RNN) based caption decoder that generates the output caption words based on the visual features with the attention mechanism. Despite the success of existing studies, current methods only model the co-attention that characterizes the inter-modal interactions while neglecting the self-attention that characterizes the intra-modal interactions. Inspired by the success of the Transformer model in machine translation, here we extend it to a Multimodal Transformer (MT) model for image captioning. Compared to existing image captioning approaches, the MT model simultaneously captures intra- and inter-modal interactions in a unified attention block. Due to the in-depth modular composition of such attention blocks, the MT model can perform complex multimodal reasoning and output accurate captions. Moreover, to further improve the image captioning performance, multi-view visual features are seamlessly introduced into the MT model. We quantitatively and qualitatively evaluate our approach using the benchmark MSCOCO image captioning dataset and conduct extensive ablation studies to investigate the reasons behind its effectiveness. The experimental results show that our method significantly outperforms the previous state-of-the-art methods. With an ensemble of seven models, our solution ranks the 1st place on the real-time leaderboard of the MSCOCO image captioning challenge at the time of the writing of this paper.
Visual question answering (VQA) is challenging, because it requires a simultaneous understanding of both visual content of images and textual content of questions. To support the VQA task, we need to ...find good solutions for the following three issues: 1) fine-grained feature representations for both the image and the question; 2) multimodal feature fusion that is able to capture the complex interactions between multimodal features; and 3) automatic answer prediction that is able to consider the complex correlations between multiple diverse answers for the same question. For fine-grained image and question representations, a "coattention" mechanism is developed using a deep neural network (DNN) architecture to jointly learn the attentions for both the image and the question, which can allow us to reduce the irrelevant features effectively and obtain more discriminative features for image and question representations. For multimodal feature fusion, a generalized multimodal factorized high-order pooling approach (MFH) is developed to achieve more effective fusion of multimodal features by exploiting their correlations sufficiently, which can further result in superior VQA performance as compared with the state-of-the-art approaches. For answer prediction, the Kullback-Leibler divergence is used as the loss function to achieve precise characterization of the complex correlations between multiple diverse answers with the same or similar meaning, which can allow us to achieve faster convergence rate and obtain slightly better accuracy on answer prediction. A DNN architecture is designed to integrate all these aforementioned modules into a unified model for achieving superior VQA performance. With an ensemble of our MFH models, we achieve the state-of-the-art performance on the large-scale VQA data sets and win the runner-up in VQA Challenge 2017.
Prenatal diagnosis of congenital heart disease (CHD) relies primarily on fetal echocardiography conducted at mid‐gestational age—the sensitivity of which varies among centers and practitioners. ...An objective method for early diagnosis is needed. Here, we conducted a case–control study recruiting 103 pregnant women with healthy offspring and 104 cases with CHD offspring, including VSD (42/104), ASD (20/104), and other CHD phenotypes. Plasma was collected during the first trimester and proteomic analysis was performed. Principal component analysis revealed considerable differences between the controls and the CHDs. Among the significantly altered proteins, 25 upregulated proteins in CHDs were enriched in amino acid metabolism, extracellular matrix receptor, and actin skeleton regulation, whereas 49 downregulated proteins were enriched in carbohydrate metabolism, cardiac muscle contraction, and cardiomyopathy. The machine learning model reached an area under the curve of 0.964 and was highly accurate in recognizing CHDs. This study provides a highly valuable proteomics resource to better recognize the cause of CHD and has developed a reliable objective method for the early recognition of CHD, facilitating early intervention and better prognosis.
Synopsis
Mass spectrometry‐based proteomics for plasma proteome profiling were performed on early gestational pregnant women with or without congenital heart disease (CHD) offspring. In‐depth analysis revealed a potential pathogenic mechanism and identified a set of biomarkers in early gestational plasma predicting fetal CHD.
A total of 104 early gestational pregnant women with CHD offspring and 103 controls with healthy offspring were included.
A total of 264 proteins were found significantly upregulated and 358 proteins downregulated in the plasma of early gestational pregnant women with CHD offspring.
Dyslipidemia and CD4+ might be involved in the occurrence of CHD.
Nine CHD‐related biomarkers had been identified.
Mass spectrometry‐based proteomics for plasma proteome profiling was performed on early gestational pregnant women with or without congenital heart disease (CHD) offspring. In‐depth analysis revealed a potential pathogenic mechanism and identified a set of biomarkers in early gestational plasma predicting fetal CHD.
A series of nonpharmaceutical interventions (NPIs) was launched in Beijing, China, on January 24, 2020, to control coronavirus disease 2019. To reveal the roles of NPIs on the respiratory syncytial ...virus (RSV), respiratory specimens collected from children with acute respiratory tract infection between July 2017 and Dec 2021 in Beijing were screened by capillary electrophoresis‐based multiplex PCR (CEMP) assay. Specimens positive for RSV were subjected to a polymerase chain reaction (PCR) and genotyped by G gene sequencing and phylogenetic analysis using iqtree v1.6.12. The parallel and fixed (paraFix) mutations were analyzed with the R package sitePath. Clinical data were compared using SPSS 22.0 software. Before NPIs launched, each RSV endemic season started from October/November to February/March of the next year in Beijing. After that, the RSV positive rate abruptly dropped from 31.93% in January to 4.39% in February 2020; then, a dormant state with RSV positive rates ≤1% from March to September, a nearly dormant state in October (2.85%) and November (2.98%) and a delayed endemic season in 2020, and abnormal RSV positive rates remaining at approximately 10% in summer until September 2021 were detected. Finally, an endemic RSV season returned in October 2021. There was a game between Subtypes A and B, and RSV‐A replaced RSV‐B in July 2021 to become the dominant subtype. Six RSV‐A and eight RSV‐B paraFix mutations were identified on G. The percentage of severe pneumonia patients decreased to 40.51% after NPIs launched. NPIs launched in Beijing seriously interfered with the endemic season of RSV.
To compare the safety and efficacy of robotic-assisted distal pancreatectomy (RADP) and laparoscopic distal pancreatectomy (LDP).
A literature search of PubMed, EMBASE, and the Cochrane Library ...database up to June 30, 2015 was performed. The following key words were used: pancreas, distal pancreatectomy, pancreatic, laparoscopic, laparoscopy, robotic, and robotic-assisted. Fixed and random effects models were applied. Study quality was assessed using the Newcastle-Ottawa Scale.
Seven non-randomized controlled trials involving 568 patients met the inclusion criteria. Compared with LDP, RADP was associated with longer operating time, lower estimated blood loss, a higher spleen-preservation rate, and shorter hospital stay. There was no significant difference in transfusion, conversion to open surgery, R0 resection rate, lymph nodes harvested, overall complications, severe complications, pancreatic fistula, severe pancreatic fistula, ICU stay, total cost, and 30-day mortality between the two groups.
RADP is a safe and feasible alternative to LDP with regard to short-term outcomes. Further studies on the long-term outcomes of these surgical techniques are required.
To date, there is no consensus on whether laparoscopic or robotic-assisted distal pancreatectomy is more beneficial to the patient. This is the first meta-analysis to compare laparoscopic and robotic-assisted distal pancreatectomy. We found that robotic-assisted distal pancreatectomy was associated with longer operating time, lower estimated blood loss, a higher spleen-preservation rate, and shorter hospital stay. There was no significant difference in transfusion, conversion to open surgery, overall complications, severe complications, pancreatic fistula, severe pancreatic fistula, ICU stay, total cost, and 30-day mortality between the two groups.
Soaring homeownership and housing prices have made it more difficult for newcomers to climb the housing ladder without parental support. This study relies on China Household Finance Survey microdata ...in 2015 to examine the role of parental attributes (PA) and financial support on adult children's homeownership attainment. Results show that, after controlling for covariates, parental lending for housing would triple the adult children's odds of homeownership. Parental financial support plays a marginal role in maintaining homeownership. Adult children are more likely to transfer income to their parents than to receive, which is detrimental to the adult children's homeownership. The relative importance of PA is secondary to that of parental support and the adult children's institutional attributes-hukou status and access to housing provident fund. While the housing market is maturing, some advantages embedded in the socialist institutional arrangements have persisted. Young adults and rural migrants, who are burdened by financially supporting their parents, will struggle more in their housing careers.
The synthesis and structure of the first 1,2‐bis(NHSi)‐substituted ortho‐carborane (LSi:)C2B10H10 (termed SiCCSi) is reported (NHSi=N‐heterocyclic silylene; L=PhC(NtBu)2). Its suitability to serve as ...a reliable bis(silylene) chelating ligand for transition metals is demonstrated by the formation of SiCCSiNiBr2 and SiCCSiNi(CO)2 complexes. The CO stretching vibration modes of the latter indicate that the SiII atoms in the SiCCSi ligand are even stronger σ donors than the PIII atoms in phosphines and CII atoms in N‐heterocyclic carbene (NHC) ligands. Moreover, the strong donor character of the SiCCSi ligand enables SiCCSiNiBr2 to act as an outstanding precatalyst (0.5 mol % loading) in the catalytic aminations of arenes, surpassing the activity of previously known molecular Ni‐based precatalysts (1–10 mol %).
The right bite: A chelating bis‐N‐heterocyclic silylene ligand bridged by an o‐carborane (SiCCSi) and its corresponding Ni complexes (see example) were synthesized, fully characterized, and successfully applied in Ni‐catalyzed Buchwald–Hartwig coupling reactions. SiCCSiNiBr2 is the most active precatalyst for this transformation that has been reported to date.
Burgers-type equations are used to describe certain phenomena in gas dynamics, traffic flow, plasma astrophysics and ocean dynamics. In this paper, a (2
+
1)-dimensional generalized Burgers system ...with the variable coefficients in a fluid is investigated. We obtain the Painlevé-integrable constraints of the system with respect to the variable coefficients. Based on the truncated Painlevé expansions, an auto-Bäcklund transformation is constructed, along with some soliton solutions. Via a truncated Painlevé expansions, certain multiple kink solutions are derived. Via a complex-conjugate transformation, some breather solutions, half-periodic kink solutions and hybrid solutions composed of the breathers and kink waves are seen.
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